There are many difficult challenges ahead in the design of an energy-efficient communication stack for wireless sensor networks. Due to the severe sensor node constraints, protocols have to be simple yet scalable. To this end, collective social insects' behavior could be adopted to guide the design of these protocols. We exploit the simple heuristics of ant colony in foraging and brood sorting to design a hierarchical and scalable data gathering protocol. Also, we demonstrate how it could exploit data correlations in sensor readings to minimize communications cost in the data gathering process towards the sink. This approach selects only a subset of sensor nodes to reconstruct data for the entire network. A distributed variance estimation algorithm is introduced to capture data correlations with negligible state maintenance. It is shown that this algorithm is able to predict the values rather accurately. Due to the general robustness of any nature-inspired algorithm, our data gathering protocol is reliable. It is fully distributed, and promises scalability and substantial energy savings.